| Title: | Do genetic variants directly shape population-level schizophrenia burden? A global genomic analysis |
| Journal: | Biological Psychiatry Global Open Science |
| Published: | 1 Mar 2026 |
| DOI: | https://doi.org/10.1016/j.bpsgos.2026.100727 |
Publication 18242
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Abstract
Background Schizophrenia imposes a substantial global health burden, with marked geographic variation in incidence, prevalence, and disability-adjusted life years (DALYs). Although genome-wide association studies (GWAS) have identified numerous individual-level risk variants, it remains unclear whether cross-population differences in allele frequencies are associated with variation in population-level disease burden. Methods We integrated allele frequencies from the 1000 Genomes Project with age-standardised incidence (ASIR), prevalence (ASPR), and DALY rates (ASDR) across 20 countries (1990-2021) using Global Burden of Disease 2021 data. Associations between allele frequencies and burden metrics were evaluated using linear mixed-effects models. Independent signals were defined through linkage disequilibrium-based clumping and annotated via multi-omic gene prioritisation. Polygenic risk score (PRS) analyses were conducted in the UK Biobank for validation. Results We identified 20, 20, and 14 independent SNPs significantly associated with ASIR, ASPR, and ASDR, respectively. Two loci overlapped with Psychiatric Genomics Consortium GWAS findings, including variants within ADGRV1 and upstream of STAG1. These loci collectively explained a meaningful proportion of cross-country variation (partial R2 = 0.13-0.22). Implicated genes (e.g., LRRC4C, GPC5, PVALB) are involved in neurodevelopmental and synaptic processes. In UK Biobank analyses, schizophrenia cases exhibited higher PRSs derived from ASIR- and ASPR-associated SNPs (P = 0.0024 and 0.0095). Conclusions These findings suggest that population-level allele frequency variation is associated with global differences in schizophrenia burden and accounts for a meaningful proportion of cross-population variation. This transferable population-genomic epidemiological framework may inform future research on complex diseases and mental health disparities. Plain Language Schizophrenia shows substantial geographic variation worldwide. This study investigates whether differences in allele frequencies across populations are associated with national measures of disease burden. By combining genomic and global health data, the authors report statistical associations between certain genetic variants and cross-country differences in schizophrenia rates. The findings highlight a potential link between population genomics and global mental health patterns.</p>
27 Authors
- Junxian Tao
- Haiyan Chen
- Siyu Wei
- Yuping Zou
- Chen Sun
- Jing Xu
- Lian Duan
- Yuanbo Zhan
- Ruilin Li
- Jiacheng Wang
- Linna Yuan
- Wei She
- Songlin Lu
- Ning Wang
- Qinduo Ren
- Yan Guo
- Yuan Xu
- Chang Wang
- Hongsheng Tian
- Chen Zhang
- Yu Dong
- Guoping Tang
- Zhenwei Shang
- Wenhua Lv
- Mingming Zhang
- Hongchao Lv
- Yongshuai Jiang
1 Application
| Application ID | Title |
|---|---|
| 89695 | Study on the interactions among genotype, phenotype, drug response and environment |
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